System and method for mapping electrophysiology information onto complex geometry

ABSTRACT

The instant invention relates to an electrophysiology apparatus and method used to measure electrical activity occurring in a portion of tissue of a patient and to visualize the electrical activity and/or information related to the electrical activity. In particular, the instant invention relates to three-dimensional mapping of the electrical activity and/or the information related to the electrical activity.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.11/647,276, filed 29 Dec. 2006, which claims the benefit of UnitedStates provisional patent application no. 60/800,848, filed 17 May 2006.Each of the foregoing is incorporated by reference as though fully setforth herein.

The following applications are also incorporated by reference as thoughfully set forth herein: U.S. application Ser. Nos. 11/227,006, filed 15Sep. 2005; 10/819,027, filed 6 Apr. 2004; 11/647,275, filed 29 Dec.2006, which claims the benefit of U.S. provisional application No.60/800,858, filed 17 May 2006; and 11/647,298, filed 29 Dec. 2006, whichclaims the benefit of United States provisional application no.60/851,042, filed 12 Oct. 2006, and which is a continuation-in-part ofU.S. application Ser. No. 11/139,908, filed 27 May 2005, which claimsthe benefit of U.S. provisional application Ser. No. 60/575,411, filed28 May 2004.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The instant invention relates to an electrophysiology apparatus andmethod used to measure electrical activity occurring in a portion oftissue of a patient and to visualize the electrical activity and/orinformation related to the electrical activity. In particular, theinstant invention relates to three-dimensional mapping of the electricalactivity and/or the information related to the electrical activity.

2. Background Art

The present invention relates to the creation of electrophysiologicalmaps of the human anatomy, including for example, an electrophysiologymap of the human heart.

Conventional modeling systems exist for generating a three-dimensionalmodel of the heart utilizing technology such as CT scan, MRI, radarimaging, x-ray imaging, and fluoroscopic imaging. Such data is oftenprocessed using a three-dimensional modeling technique. Such imagingtechnology is often useful in preparing a patient for treatment and/orsurgery, and typically, the imaging process is performed hours and insome cases days in advance of the treatment and/or surgery.

During the treatment and/or surgery, conventional systems are availablethat can generate an electrophysiology map for the patient. Anelectrophysiology map is especially useful in connection with thediagnosis and treatment of atrial fibrillation of a patient's heart. Thepoints at which the electrophysiology data is measured, however, rarelycorrespond to the data points that define the three-dimensional modelprepared in advance of the treatment.

Accordingly, a need exists for an improvement that can relateelectrophysiology data to a three-dimensional surface model of apatient's anatomy.

BRIEF SUMMARY OF THE INVENTION

The present invention expands the previous capabilities of cardiacelectrophysiology mapping systems by providing the ability to mapelectrophysiology measurements directly to previously obtainedthree-dimensional images.

The present invention provides the ability to utilize high resolutionimage data together with electrophysiology measurements taken at thetime of treatment. Thus, the present invention permits the blending ofdifferent technologies for an improved treatment.

The foregoing and other aspects, features, details, utilities, andadvantages of the present invention will be apparent from reading thefollowing description and claims, and from reviewing the accompanyingdrawings.

Embodiments of the present invention provide a method for mappingelectrophysiological information on a three-dimensional model comprisingthe steps of: A) obtaining a three-dimensional model of at least aportion of a heart comprising position information for a plurality oflocation points on a surface of the heart; B) obtaining a cardiacelectrophysiology map comprising position information for a plurality ofmeasurement points and electrophysiology measurements made at each ofthe plurality of measurement points; C) choosing a location point fromthe plurality of location points in the three-dimensional model anddetermining the two closest measurement points from the cardiacelectrophysiology map; D) defining a Delaunay edge between the twomeasurement points determined to be closest to the chosen locationpoint; repeating steps C) and D) for each of the plurality of locationpoints in the three-dimensional model, to define a plurality of Delaunayedges connecting at least some of the plurality of measurement pointswithin the cardiac electrophysiology map; F) connecting the Delaunayedges to form a plurality of triangles; and G) identifying one of theplurality of location points from the three dimensional model,identifying one of the plurality of triangles whose edges surround theidentified location point, and assigning an electrophysiology level tothe identified location point based on interpolation using theelectrophysiology measurements measured at each of the vertices of theidentified triangle.

The methods further optionally include assigning a color or grayscale toeach individual location point of a plurality of location points in thethree-dimensional model based on a relative magnitude of theelectrophysiology level assigned to the individual location point, andpresenting the three-dimensional model using the colors assigned to theplurality of location points in the three-dimensional model, in theinstance where electrophysiology levels have been assigned to aplurality of location points.

Optionally, the step of obtaining a cardiac electrophysiology mapfurther includes inserting an electrode within a portion of a heart;placing the electrode at a plurality of measurement points along asurface of the heart; receiving position information for each of theplurality of measurement points along a surface of the heart; receivingelectrophysiology measurements at each of the plurality of measurementpoints; and associating the electrophysiology measurements with therespective measurement points at which the electrophysiologymeasurements were measured.

Optionally, the step of obtaining a three-dimensional model of at leasta portion of a heart further includes inserting an electrode within aportion of a heart; placing the electrode at a plurality of locationpoints along a surface of the heart; receiving position information foreach of the plurality of location points along a surface of the heart;and generating a three-dimensional model of at least a portion of aheart comprising position information for each of the plurality oflocation points along the surface of the heart.

Optionally, the step of obtaining a three-dimensional model of at leasta portion of a heart further includes inserting an electrode within aportion of a heart; placing the electrode at a first plurality oflocation points along a surface of the heart; receiving positioninformation for each of the first plurality of location points along asurface of the heart; generating a preliminary three-dimensionalgeometry of the at least a portion of the heart comprising positioninformation for each of the first plurality of location points along thesurface of the heart; and processing the preliminary three-dimensionalgeometry to create a three-dimensional model comprising positioninformation for each of a second plurality of location points, whereinthe second plurality includes at least some of the location points fromthe first plurality of location points.

Optionally, the step of processing the preliminary three-dimensionalgeometry to create a three-dimensional model may include processing thepreliminary three-dimensional geometry to create a three-dimensionalmodel having position information for each of a second plurality oflocation points, wherein the three-dimensional model has a finerresolution than the preliminary three-dimensional geometry such that thesecond plurality of location points is greater in number than the firstplurality of location points. The step of processing the preliminarythree-dimensional geometry may also include processing the preliminarythree-dimensional geometry with a smoothing algorithm to create athree-dimensional model having position information for each of a secondplurality of location points. The three-dimensional model may be createdusing technology including CT scan, MRI, radar imaging, x-ray imaging,fluoroscopic imaging, infrared imaging, ultrasonic imaging, andcombinations thereof.

Optionally, the step of choosing a location point from the plurality oflocation points in the three-dimensional model and determining the twoclosest measurement points from the cardiac electrophysiology map mayfurther include choosing a location point from the plurality of locationpoints in the three-dimensional model, and using a Kirsanov-Hoppegeodesic algorithm to determine the two measurement points in thecardiac electrophysiology map that are closest in distance to the chosenlocation point. Additionally, the step of connecting the Delaunay edgesinto triangles may further include creating additional triangles usingmeasurement points that are not already connected to a Delaunay edge.

Optionally, the step of choosing a location point from the plurality oflocation points in the three-dimensional model and determining the twoclosest measurement points from the cardiac electrophysiology map mayinclude choosing a location point from the plurality of location pointsin the three-dimensional model, and using a Fast Marching geodesicalgorithm to determine the two measurement points in the cardiacelectrophysiology map that are closest in distance to the chosenlocation point.

According to another embodiment of the present invention, a method formapping electrophysiological information on a three-dimensional model isprovided comprising the following steps: A) obtaining athree-dimensional model of at least a portion of a heart comprisingposition information for a plurality of location points on a surface ofthe heart; B) obtaining a cardiac electrophysiology map comprisingposition information for a plurality of measurement points andelectrophysiology measurements made at each of the plurality ofmeasurement points; C) choosing a location point from the plurality oflocation points in the three-dimensional model and determining twomeasurement points from the cardiac electrophysiology map that areclosest to the chosen location point; D)defining a Delaunay edge betweenthe two measurement points determined to be closest to the chosenlocation point; E) repeating steps C) and D) for each of the pluralityof location points in the plurality of location points, to define aplurality of Delaunay edges connecting at least some of the plurality ofmeasurement points within the cardiac electrophysiology map;F)connecting the Delaunay edges into triangles to create a triangulatedmodel, and filling any gaps in the triangulated model with newtriangles; G) identifying at least one location point that is closer toa measurement point than to any point on the nearest Delaunay edge, andassigning an electrophysiology level to the at least one location pointwhere the assigned electrophysiology level is the same as theelectrophysiology measurements measured at the measurement point; and H)assigning an electrophysiology level to at least one location pointlocated inside a triangle, based on interpolation, e.g., barycentricinterpolation, using the electrophysiology measurements measured at eachof the vertices of the triangle.

According to yet another embodiment of the present invention, a systemfor mapping electrophysiological information on a three-dimensionalmodel includes: a modeling processor to generate a three-dimensionalmodel of at least a portion of a heart comprising position informationfor a plurality of location points on a surface of the heart; anelectrophysiology measurement device for generating a cardiacelectrophysiology map comprising position information for a plurality ofmeasurement points and electrophysiology measurements made at each ofthe plurality of measurement points, the electrophysiology measurementsbeing associated with the respective measurement points at which theelectrophysiology measurements were measured; a Delaunay edge processorto process a subset of the plurality of location points in thethree-dimensional model and to determine, for each location point beingprocessed, the two measurement points in the cardiac electrophysiologymap that are closest in distance to location point being processed, saidprocessor defining a plurality of Delaunay edges, each of whichcomprises the pairs of measurement points determined to be closest toeach of the location points being processed; a triangulation processorto define a plurality of triangles within the cardiac electrophysiologymap based on the plurality of Delaunay edges; and a projection processorto assign an electrophysiology level to at least one location pointlocated within one of the plurality of triangles based on interpolationusing the electrophysiology measurements associated with each of thevertices of the triangle.

Optionally, the processor assigns an electrophysiology level to at leastone location point located that is within a proximity threshold of aDelaunay edge based on bilinear interpolation using theelectrophysiology measurements measured at endpoints of the Delaunayedge.

Optionally, the processor also assigns an electrophysiology level to atleast one location point based on the electrophysiology measurementsmeasured at a measurement point that is within a proximity threshold,wherein the electrophysiology level being assigned is the same as thatof the measurement point.

According to another embodiment of the present invention a method formapping electrophysiological information on a three-dimensional model isprovided comprising the following steps: A) obtaining athree-dimensional model of at least a portion of a heart comprisingposition information for a plurality of location points on a surface ofthe heart; B) obtaining a cardiac electrophysiology map comprisingposition information for a plurality of measurement points andelectrophysiology measurements made at each of the plurality ofmeasurement points; C) choosing a location point from the plurality oflocation points in the three-dimensional model and determining the twoclosest measurement points from the cardiac electrophysiology map; D)defining an edge between the two measurement points determined to beclosest to the chosen location point; E) repeating steps C) and D) foreach of the plurality of location points in the three-dimensional model,to define a plurality of edges connecting at least some of the pluralityof measurement points within the cardiac electrophysiology map; F)connecting the edges to form a plurality of polygons; and G) identifyingone of the plurality of location points from the three dimensionalmodel, identifying one of the plurality of polygons whose edges surroundthe identified location point, and assigning an electrophysiology levelto the identified location point based on interpolation using theelectrophysiology measurements measured at each of the vertices of theidentified polygon.

According to yet another embodiment of the present invention, a systemfor mapping electrophysiological information on a three-dimensionalmodel is providing comprising a surface modeling controller to obtain athree-dimensional model of at least a portion of a heart comprisingposition information for a plurality of location points on a surface ofthe heart; an electrophysiology measurement device for generating acardiac electrophysiology map comprising position information for aplurality of measurement points and electrophysiology measurements madeat each of the plurality of measurement points, said electrophysiologymeasurements being associated with the respective measurement points atwhich the electrophysiology measurements were measured; an edgeprocessor to process a subset of the plurality of location points in thethree-dimensional model and to determine, for each location point beingprocessed, the two measurement points in the cardiac electrophysiologymap that are closest in distance to location point being processed, saidprocessor defining a plurality of edges, each of which comprises thepairs of measurement points determined to be closest to each of thelocation points being processed; a geometry processor to define aplurality of polygons within the cardiac electrophysiology map based onthe plurality of edges; and a mapping projector to assign anelectrophysiology level to at least one location point located withinone of the plurality of polygons based on interpolation using theelectrophysiology measurements associated with each of the vertices ofthe polygons.

Optionally, the processor also assigns an electrophysiology level to atleast one location point located near an edge based on bilinearinterpolation using the electrophysiology measurements measured atendpoints of the edge.

Optionally, the geometry processor defines the cardiac electrophysiologymap using a plurality of triangles. The mapping projector assigns anelectrophysiology level to at least one location point located withinone of the triangles based on interpolation using the electrophysiologymeasurements associated with each of the vertices of the triangle.

Yet another embodiment of the present invention provides a computerizedmethod for mapping electrophysiological information on athree-dimensional model comprising the following steps: A) receiving athree-dimensional model of at least a portion of an anatomy comprisingposition information for a plurality of location points on a surface ofthe anatomy; B) receiving an electrophysiology map for the anatomycomprising position information for a plurality of measurement pointsand electrophysiology measurements made at each of the plurality ofmeasurement points; C) using a computer to determine, for eachindividual location point of the plurality of location points in thethree-dimensional model, the two measurement points from theelectrophysiology map that are closest to the individual location pointand then defining an edge comprising the determined pair of measurementpoints; D) using the computer to connecting the edges to form a mesh ofclosed polygons; E) using the computer to identify location points fromthe three dimensional model that lie on a surface of a closed polygonswhose edges surround the identified location point, wherein the computerassigning an electrophysiology level to the identified location pointbased on interpolation using the electrophysiology measurements measuredat each of the vertices of the polygons whose edges surround theidentified location point; and F) outputting an output file comprisingposition information for a plurality of location points andelectrophysiology levels that were assigned to each of the plurality oflocation points.

In accordance with another embodiment of the present invention, a methodfor mapping electrophysiological information on a three-dimensionalmodel is provided comprising the following steps: A) obtaining athree-dimensional model of at least a portion of a heart comprisingposition information for a plurality of location points on a surface ofthe heart; B) obtaining a cardiac electrophysiology map comprisingposition information for a plurality of measurement points andelectrophysiology measurements made at each of the plurality ofmeasurement points; C) processing the three-dimensional model usingtriangulation so as to create a subdivided three-dimensional modelcomprising a plurality of triangles in which each of the plurality ofmeasurement points are vertices; and D) processing the subdividedthree-dimensional model using a decimation algorithm to generate arevised three-dimensional model comprising a second plurality oftriangles, wherein each of the plurality of measurement points is avertex for a triangle.

Optionally, the triangulation processing step is programmed to disallowthe creation of triangular edges which are longer than a predetermineddistance threshold.

This embodiment may further include the step of projecting theelectrophysiology measurements for a measurement point upon a vertex oredge of the subdivided three-dimensional model using a Kirsanov-Hoppe orFast Marching geodesic algorithm.

Optionally, this embodiment may further include the step of assigning acolor or grayscale to each vertex of the revised three-dimensional modelbased on a relative magnitude of the electrophysiology level assigned;and presenting the revised three-dimensional model using the colorsassigned to the plurality of vertices in the revised three-dimensionalmodel.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a system for performing a cardiacelectrophysiology examination or ablation procedure wherein the locationof one or more electrodes can be determined and recorded.

FIG. 2 is a schematic representation of a heart investigated by anelectrophysiology catheter with several distal electrodes.

FIG. 3 is a schematic diagram of an exemplary methodology for renderinga surface of a heart cavity using recorded electrode position datapoints.

FIG. 4 is a schematic depiction of a graphical user interface fordisplaying electrocardiograph and related electrophysiologicalinformation to a clinician.

FIG. 5 is an enlargement of the panel 66 depicted in FIG. 4.

FIG. 6 shows side-by-side views of time-varying electrograms collectedfor various locations along a wall of a heart.

FIG. 7 shows side-by-side views of time-varying electrograms collectedfor various locations along a wall of a heart.

FIG. 8 shows side-by-side comparisons of electrograms for typicalcompact and fibrillar myocardial muscle tissues in the time-domain andfrequency-domain.

FIG. 9A shows a side-by-side comparison of time-domain andfrequency-domain information for electrograms.

FIG. 9B shows a side-by-side comparison of time-domain andfrequency-domain information for electrograms with energy in multiplespectral bands shown in cross-hatch.

FIG. 10 shows a method for collecting electrograms and mappingtime-domain and/or frequency-domain electrogram information on athree-dimensional model.

FIG. 11 illustrates a three-dimensional model of a portion of a heart.An identical color version of FIG. 11 (without reference numbers) isalso submitted herewith.

FIG. 12 illustrates an electrophysiology data map for the same portionof the heart shown in FIG. 11. An identical color version of FIG. 12(without reference numbers) is also submitted herewith.

FIG. 13 contains the three-dimensional model of FIG. 11 upon whichdistance lines have been drawn from midpoints that are measured usingFIG. 12. An identical color version of FIG. 13 (without referencenumbers) is also submitted herewith.

FIG. 14 shows a voltage map for the same portion of the heart as shownin FIG. 11, in which the electrophysiology data map from FIG. 12 hasbeen projected on to the three-dimensional model of FIG. 11. Anidentical color version of FIG. 14 (without reference numbers) is alsosubmitted herewith.

DETAILED DESCRIPTION OF THE INVENTION

The present invention improves a system's ability to create an improvedelectrophysiology mapping of an anatomy. The present invention is notlimited to creating accurate models of the heart, but for illustrativepurposes, reference will often be made herein to a navigation andlocalization system used for assessment and treatment of cardiac tissue.The methodology described herein would be equally applicable to modelingother parts of the human anatomy. For purposes of illustrating thepresent invention, the techniques for creating an electrophysiology mapof a cardiac tissue will be described below.

Many conventional systems exist for generating a three-dimensional modelof the heart, including systems that utilize technology such as CTscanning, MRI, ultrasound imaging, radar imaging, x-ray imaging, andfluoroscopic imaging. The output of such data may be a plurality ofx-y-z data coordinates, spherical coordinates and/or other formats toprovide a three-dimensional image. Such imaging technology is oftenuseful in diagnosis as well as preparing for a patient's treatmentand/or surgery. Sometimes, the imaging process is performed hours beforeand in some cases days in advance of the treatment and/or surgery.

Of course, the three-dimensional model may utilize a segmented approach,including for example, a segmented CT or MRI scan image. A segmentedmodel indicates that a subregion of a three-dimensional image has beendigitally separated from a larger three-dimensional image, e.g., animage of the right atrium separated from the rest of the heart. Othermethodologies and techniques for creating a three-dimensional model of aportion of the patient may also be utilized in accordance with thepresent invention, including for example, the methodologies andtechniques disclosed in U.S. Pat. No. 6,728,562 (“the '562 patent”), thecontent of which is hereby incorporated by reference in its entirety.

Still other techniques to create a three-dimensional model of theanatomy will be discussed further below.

Techniques available to develop an electrophysiology map will now bediscussed in connection with FIG. 1, which shows a schematic diagram ofa localization system 8 for conducting cardiac electrophysiology studiesby navigating a cardiac catheter and measuring electrical activityoccurring in a heart 10 of a patient 11 and three-dimensionally mappingthe electrical activity and/or information related to or representativeof the electrical activity. System 8 can be used to help create ananatomical model using one or more electrodes. System 8 can also be usedto measure electrophysiology data at a plurality of points along acardiac surface, and store the measured data in association withlocation information for each measurement point at which theelectrophysiology data was measured.

The patient 11 is depicted schematically as an oval for simplicity.Three sets of surface electrodes (e.g., patch electrodes) are shownapplied to a surface of the patient 11 along an X-axis, a Y-axis, and aZ-axis. The X-axis surface electrodes 12, 14 are applied to the patientalong a first axis, such as on the lateral sides of the thorax region ofthe patient (e.g., applied to the patient's skin underneath each arm)and may be referred to as the Left and Right electrodes. The Y-axiselectrodes 18, 19 are applied to the patient along a second axisgenerally orthogonal to the X-axis, such as along the inner thigh andneck regions of the patient, and may be referred to as the Left Leg andNeck electrodes. The Z-axis electrodes 16, 22 are applied along a thirdaxis generally orthogonal to the X-axis and the Y-axis, such as alongthe sternum and spine of the patient in the thorax region and may bereferred to as the Chest and Back electrodes. The heart 10 lies betweenthese pairs of surface electrodes. An additional surface referenceelectrode (e.g., a “belly patch”) 21 provides a reference and/or groundelectrode for the system 8. The belly patch electrode 21 is analternative to a fixed intra-cardiac electrode 31. It should also beappreciated that, in addition, the patient 11 will have most or all ofthe conventional electrocardiogram (ECG) system leads in place. This ECGinformation is available to the system 8 although not illustrated in theFIG. 1.

In a preferred embodiment, the localization/mapping system is the EnSiteNavX™ navigation and visualization system of St. Jude Medical, AtrialFibrillation Division, Inc. Other localization systems, however, may beused in connection with the present invention, including for example,the CARTO navigational and location system of Biosense Webster, Inc. andthe LOCALISA intracardiac navigation system of Medtronic, Inc. Thelocalization and mapping systems described in the following patents (allof which are hereby incorporated by reference in their entireties) canbe used with the present invention: U.S. Pat. Nos. 6,990,370; 6,978,168;6,947,785; 6,939,309; 6,728,562; 6,640,119; 5,983,126; and 5,697,377.

A representative catheter 13 having at least one electrode 17 (e.g., adistal electrode) is also shown. This representative catheter electrode17 is referred to as the “roving electrode” or “measurement electrode”throughout the specification. Typically, multiple electrodes on catheter13, or on multiple such catheters, will be used. In one embodiment, forexample, the system 8 may comprise up to sixty-four electrodes on up totwelve catheters disposed within the heart and/or vasculature of thepatient. Of course, this embodiment is merely exemplary, and any numberof electrodes and catheters may be used within the scope of the presentinvention.

An optional fixed reference electrode 31 (e.g., attached to a wall ofthe heart 10) is also shown on a second catheter 29. For calibrationpurposes, this electrode 31 may be stationary (e.g., attached to or nearthe wall of the heart) or disposed in a fixed spatial relationship withthe roving electrode 17. The fixed reference electrode 31 may be used inaddition or alternatively to the surface reference electrode 21described above. In many instances, a coronary sinus electrode or otherfixed electrode in the heart 10 can be used as a reference for measuringvoltages and displacements.

Each surface electrode is coupled to the multiplex switch 24 and thepairs of electrodes are selected by software running on a computer 20,which couples the electrodes to a signal generator 25. The computer 20,for example, may comprise a conventional general-purpose computer, aspecial-purpose computer, a distributed computer, or any other type ofcomputer. The computer 20 may comprise one or more processors, such as asingle central-processing unit, or a plurality of processing units,commonly referred to as a parallel processing environment.

Generally, three nominally orthogonal electric fields are generated by aseries of driven and sensed electric dipoles in order to realizecatheter navigation in a biological conductor. Alternately, theseorthogonal fields can be decomposed and any pairs of surface electrodescan be driven as dipoles to provide effective electrode triangulation.Additionally, such nonorthogonal methodologies add to the flexibility ofthe system. For any desired axis, the potentials measured across anintra-cardiac electrode 17 resulting from a predetermined set of drive(source-sink) configurations are combined algebraically to yield thesame effective potential as would be obtained by simply driving auniform current along the orthogonal axes.

Thus, any two of the surface electrodes 12, 14, 16, 18, 19, 22 may beselected as a dipole source and drain with respect to a groundreference, e.g., the belly patch 21, while the unexcited electrodesmeasure voltage with respect to the ground reference. The measurementelectrode 17 placed in the heart 10 is exposed to the field from acurrent pulse and is measured with respect to ground, e.g., the bellypatch 21. In practice the catheters within the heart may containmultiple electrodes and each electrode potential may be measured. Aspreviously noted, at least one electrode may be fixed to the interiorsurface of the heart to form a fixed reference electrode 31, which isalso measured with respect to ground. Data sets from each of the surfaceelectrodes, the internal electrodes, and the virtual electrodes may allbe used to determine the location of the measurement electrode 17 orother electrodes within the heart 10.

One of skill in the art will readily appreciate that the measurementelectrode 17 can also be used to measure electrophysiology data andsystem 8 can be used to store the electrophysiology data (e.g., voltagereadings, including without limitation, voltage variations over a periodof time) in association with location information for the measurementpoint at which the electrophysiology data was measured.

For example, all of the raw electrode voltage data is measured by theA/D converter 26 and stored by the computer 20 under the direction ofsoftware. This electrode excitation process occurs rapidly andsequentially as alternate sets of surface electrodes are selected andthe remaining non-driven electrodes are used to measure voltages. Thiscollection of voltage measurements is referred to herein as the“electrode data set.” The software has access to each individual voltagemeasurement made at each electrode during each excitation of each pairof surface electrodes.

The raw electrode data is used to determine the “base” location inthree-dimensional space (X, Y, Z) of the electrodes inside the heart,such as the roving electrode 17, and any number of other electrodeslocated in or around the heart and/or vasculature of the patient 11.FIG. 2 shows a catheter 13, which may be a conventionalelectrophysiology catheter (sometimes referred to as an “EP catheter”),extending into the heart 10. In FIG. 2, the catheter 13 extends into theleft ventricle 50 of the heart 10. The catheter 13 comprises the distalelectrode 17 discussed above with respect to FIG. 1 and has additionalelectrodes 52, 54, and 56. Since each of these electrodes lies withinthe patient (e.g., in the left ventricle of the heart), location datamay be collected simultaneously for each of the electrodes. In addition,when the electrodes are disposed adjacent to the surface, although notnecessarily directly on the surface of the heart, and when the currentsource 25 is “off” (i.e., when none of the surface electrode pairs isenergized), at least one of the electrodes 17, 52, 54, and 56 can beused to measure electrical activity (e.g., voltage) on the surface ofthe heart 10.

The data used to determine the location of the electrode(s) within theheart is measured while the surface electrode pairs impress an electricfield on the heart. A number of electrode locations may be collected byeither sampling a number (e.g., sixty-two electrodes spread among up totwelve catheters) simultaneously or in sequence (e.g., multiplexed)and/or by sampling one or more electrodes (e.g., the roving electrode17) being moved within the patient (e.g., a chamber of the heart). Inone embodiment, the location data for individual electrodes are sampledsimultaneously, which allows for collection of data at a single stage orphase of a heartbeat. In another embodiment, location data may becollected either synchronously with one or more phases of the heartbeator without regard for any particular stage of the heartbeat. Where thedata is collected across the phases of the heartbeat, data correspondingto locations along the wall of the heart will vary with time. In onevariation, the data corresponding to the outer or inner locations may beused to determine the position of the heart wall at the maximum andminimum volumes, respectively. For example, by selecting the mostexterior points it is possible to create a “shell” representing theshape of the heart at its greatest volume.

The electrode data may also be used to create a respiration compensationvalue used to improve the raw location data for the electrode locationsas described in U.S. Patent Application Publication No. 2004/0254437,which is hereby incorporated herein by reference in its entirety. Theelectrode data may also be used to compensate for changes in theimpedance of the body of the patient as described in co-pending U.S.patent application Ser. No. 11/227,580, filed on 15 Sep. 2005, which isalso incorporated herein by reference in its entirety.

In summary, the system 8 first selects a set of surface electrodes andthen drives them with current pulses. While the current pulses are beingdelivered, electrical activity, such as the voltages measured at leastone of the remaining surface electrodes and in vivo electrodes aremeasured and stored. At this point, compensation for artifacts, such asrespiration and/or impedance shifting may be performed as indicatedabove. As described above, various location data points are collected bythe system 8 that are associated with multiple electrode locations(e.g., endocardial electrode locations). Each point in the set hascoordinates in space. In one embodiment, the system 8 collects locationdata points for up to sixty-four electrodes that may be located on up totwelve catheters simultaneously or in close proximity to one another.However, smaller or larger data sets may be collected and result in lesscomplex and lower resolution or more complex and higher resolutionrepresentations of the heart, respectively.

A three-dimensional model of a portion of the patient, e.g., a region ofthe patient's heart or surrounding vasculature, may be created from thelocation data points, e.g., during the same or a previous procedure, ora previously generated three-dimensional model, e.g., a segmented CT orMRI scan image, may be used. A segmented model indicates that asubregion of a three-dimensional image has been digitally separated froma larger three-dimensional image, e.g., an image of the right atriumseparated from the rest of the heart. Exemplary segmentationapplications include ANALYZE (Mayo, Minneapolis, Minn.), Verismo (St.Jude Medical, Inc., St. Paul, Minn.), and CardEP (General ElectricMedical Systems, Milwaukee, Wis.). Where the three-dimensional model iscreated from the location data points collected by the system 8, forexample, during a single procedure by sweeping one or more electrodesover the surface of the heart, the exterior-most location points in thedata can be used to determine a shape corresponding to the volume of aregion of the patient's heart.

Other methodologies and techniques for creating three-dimensional modelsof a portion of the patient may also be utilized in accordance with thepresent invention. For example, a convex hull may be generated usingstandard algorithms such as the Qhull algorithm. The Qhull algorithm,for example, is described in Barber, C. B., Dobkin, D. P., andHuhdanpaa, H. T., “The Quickhull algorithm for convex hulls,” ACM Trans.on Mathematical Software, 22(4):469-483, December 1996. Other algorithmsused to compute a convex hull shape are known and may also be suitablefor use in implementing the invention. This surface may then bere-sampled over a more uniform grid and may be interpolated to give areasonably smooth surface stored as a three-dimensional model forpresentation to the physician during the same or a later procedure. There-sampled surface generally may have a greater number of data points.The re-sampled surface may also be processed using a smoothingalgorithm, which will give the geometry a much smoother appearance. Sucha three-dimensional model, for example, provides an estimated boundaryof the interior of the heart region from the set of points.

FIG. 3 schematically depicts another exemplary method for creating ashell corresponding to the shape of a heart chamber. The location dataidentifying position data points 40 of one or more electrodes within theheart chamber over a period of time is accessed. The location data maybe represented as a cloud of points within the heart chamber. The mostdistant position data points 40 will thus correspond to the interiorwall of the heart chamber in a relaxed or diastole state correspondingto its greatest volume. A shell or surface is rendered from thislocation data by fitting an array of “bins” 44 around groups of theposition data points 40. The bins 44 are constructed by determining amean center point 42 within the cloud of position data points 40 andthen extending borders radially outward from the center point 42. Thebins 44 extend to the furthest position data point 40 within the sliceencompassed by the bin 44. It should be noted that even though FIG. 3 isschematically presented in two dimensions, the bins 44 arethree-dimensional volumes. The radial end faces 46 of the bins 44 thusapproximate the surface of the heart chamber wall. Common graphicshading algorithms can then be employed to “smooth” the surface of theshell thus created out of the radial end faces 46 of the bins 44.

Another example of creating a three-dimensional map using a cloud ofpoints is described in U.S. application Ser. No. 11/647,275, filed 29Dec. 2006. Yet another technique for creating a three-dimensional map ofa tissue surface is described in U.S. application Ser. No. 11/647,298,filed 29 Dec. 2006.

Various electrophysiology data may be measured and presented to acardiologist through the display 23 of the system 8 shown in FIG. 1.FIG. 4 depicts an illustrative computer display that may be displayedvia the computer 20. The display 23, for example, may be used to showdata to a user, such as a physician, and to present certain options thatallow the user to tailor the configuration of the system 8 for aparticular use. It should be noted that the contents on the display canbe easily modified and the specific data presented is illustrative onlyand not limiting of the invention. An image panel 60 shows athree-dimensional model of a heart chamber 62 identifying regions thatreceived a depolarization waveform at the same time, i.e., “isochrones,”mapped to the model in false color or grayscale. The isochrones are, inone variation, mapped to three-dimensional coordinates (e.g., X, Y, Z)corresponding to the electrogram from which they were obtained. Theisochrones are also shown in guide bar 64 as a key, identifyinginformation associated with a particular color or grayscale mapped tothe three-dimensional model. In this image, the locations of multipleelectrodes on a pair of catheters are also mapped to thethree-dimensional model. Other data that may be mapped to the heartsurface model include, for example, the magnitude of a measured voltageand the timing relationship of a signal with respect to heartbeatevents. Further, the peak-to-peak voltage measured at a particularlocation on the heart wall may be mapped to show areas of diminishedconductivity and may reflect an infarcted region of the heart.

In the variation shown in FIG. 4, for example, the guide bar 64 isgraduated in milliseconds and shows the assignment of each color orgrayscale to a particular time relationship mapped to thethree-dimensional model. The relationship between the color or grayscaleon the three-dimensional model image 62 and the guide bar 64 can also bedetermined by a user with reference to the information shown in panel66. FIG. 5 shows an enlargement of the panel 66 depicted in FIG. 4. Thepanel 66, in this variation, shows timing information used to generateisochrones mapped on the three-dimensional model 62 shown in FIG. 4. Ingeneral, a fiducial point is selected as the “zero” time. In FIG. 5, forexample, the inflection point 70 of a voltage appearing on a referenceelectrode is used as the primary timing point for the creation ofisochrones. This voltage may be acquired from either a virtual referenceor a physical reference (e.g., the roving electrode 17 shown in FIG. 1).In this variation, the voltage tracing corresponding to the fiducialpoint is labeled “REF” in FIG. 5. The roving electrode signal isdepicted in FIG. 5 and is labeled “ROV.” The inflection point 72 of thevoltage signal ROV corresponds to the roving electrode 31. The colorguide bar 65 shows the assignment of color or grayscale tone for thetiming relationship seen between inflection points 70 and 72 of thereference and roving voltage signals REF and ROV, respectively.

The amplitude of the voltage signal ROV corresponding to the rovingelectrode 17 is also shown on panel 66 of FIG. 5. The amplitude of thetime-varying signal ROV is located between two adjustable bands 74 and76, which can be used to set selection criteria for the peak-to-peakvoltage of the signal ROV. In practice, regions of the heart with lowpeak-to-peak voltage are the result of infarcted tissue, and the abilityto convert the peak-to-peak voltage to grayscale or false color allowsidentification of the regions that are infarcted or ischemic. Inaddition, a time-varying signal “V1” is also shown and corresponds to asurface reference electrode, such as a conventional ECG surfaceelectrode. The signal V1, for example, may orient a user, such as aphysician, to the same events detected on the surface of the patient.

Various time-domain information related to the EP activity in and/oraround the heart of a patient may be mapped to the three-dimensionalmodel. For example, the time difference of an action potential measuredat a roving electrode and a reference electrode, the peak-to-peakvoltage of an action potential measured at the roving electrode, and/orthe peak negative voltage of an action potential measured at the rovingelectrode may be mapped to a three-dimensional model. In one embodiment,EP activity from up to sixty-two roving electrodes may be collected andmapped to the three-dimensional model.

Complex fractionated electrogram (CFE) and frequency-domain informationmay also be mapped to the three-dimensional model. CFE information, forexample, may be useful to identify and guide ablation targets for atrialfibrillation. CFE information refers to irregular electrical activation(e.g., atrial fibrillation) in which an electrogram comprises at leasttwo discrete deflections and/or perturbation of the baseline of theelectrogram with continuous deflection of a prolonged activation complex(e.g., over a 10 second period). Electrograms having very fast andsuccessive activations are, for example, consistent with myocardiumhaving short refractory periods and micro-reentry. FIG. 6, for example,shows a series of electrograms. (FIG. 6 is associated with an article byNADEMANEE, Koonlawee, M. D., FACC, et. al., A new approach for catheterablation of atrial fibrillation: Mapping of the electrophysiologicsubstrate, Journal of the American College of Cardiology, (2004) Vol.43, No. 11, 2044-53.) The first two electrograms, RAA-prox and RAA-dist,comprise typical electrograms from the right atrium of a patient such asfrom a proximal roving electrode and a distal roving electrode in theright atrium of a patient, respectively. The third electrogram, LA-roof,comprises a CFE electrogram, such as from the roof of the patient's leftatrium. In this third electrogram, LA-roof, the cycle lengths indicatedby the numbers shown in the electrogram are substantially shorter thanthe cycle lengths indicated by the numbers shown in the first twoelectrograms, RAA-prox and RAA-dist. In another example shown in FIG. 7,a first electrogram RA-Septum comprises fast and successive activationsindicated by the arrows compared to the second electrogram RA. The fastand successive activations, for example, can be consistent withmyocardial tissue having short refractory periods and micro-reentry,e.g., an atrial fibrillation “nest.”

The presence of CFE information can be detected from the EP information(e.g., electrograms) collected by an electrode, for example, bymonitoring the number of deflections within an electrogram segment;calculating the average time between deflections within an electrogramsegment; monitoring the variation of time between deflections within acycle length of an electrogram; and calculating slopes, derivatives, andamplitudes of electrograms. For example, discrete activations have anassociated peak-to-peak value measured over a specified time period.This peak-to-peak value may be used to quantify a discrete activation.As shown in FIG. 5, a time instant of the discrete activations can bemarked on the electrogram on the user display. The time instant and/orother quantifications of the fractionation of the electrogram may beused to determine the presence and/or absence of CFE information. Themean interval between discrete activations within a predetermined timeperiod may, for example, be used as an index to quantify the degree offractionation of a given electrogram. In this example, a value of onemay be assigned to the electrogram if there is only one discreteactivation within the given time period, and a lesser or higher valuemay be assigned if more than one discrete activation is present in thegiven time period. Another quantification may comprise, for example,quantifying the variance in time between discrete activations of anelectrogram. These or other quantifications of the time-domain correlatewith the morphology of the electrogram and are, in turn, based upon theunderlying physiology of the region from which the electrogram wassampled.

In diagnosing atrial fibrillation and guiding an ablation catheter, theelectrograms corresponding to physiological mechanisms for initiatingand sustaining atrial fibrillation may be identified by quantifying thefractionation of the electrograms. These quantifications, in turn, maybe used to identify regions to be ablated to eliminate the atrialfibrillation. Mid-diastolic potentials within an ischemic area of thecardiac chamber may also be identified by quantifying the fractionationof the electrograms collected in a region of the heart. Healthy tissuewould correspond to non-fractionated electrograms (i.e., a singlediscrete activation), while unhealthy tissue (e.g., ischemic tissue)would correspond to fractionated electrograms (i.e., multiple discreteactivations and/or perturbations of the baseline). The time instant orother quantifications of CFE information in electrograms may then bemapped to a three-dimensional model as described above.

In addition to and/or alternatively to the time-domain informationanalyzed and mapped from the collected EP information, frequency-domaininformation may also be mapped to a three-dimensional model. In oneembodiment, for example, a fast Fourier transform (FFT) or other methodof translating a time-varying signal into frequency-domain informationmay be used to translate the collected signal into a frequency-domain.The frequency domain depicts a spectrum that represents the energy orpower of frequency components of a time-varying electrogram signal. FFTsand other transforms are known in the art and are not discussed infurther detail herein.

FIG. 8 shows a side-by-side comparison of compact myocardial muscle andfibrillar myocardial muscle that together form the wall of the heart.Compact myocardial muscle tissue comprises groups of tightly-connectedcells that conduct electrical activity during depolarization of theheart in a homogenous fashion by transmitting electrical activity atequal speeds in any direction. Fibrillar myocardial muscle tissue,however, typically comprises loosely connected cells, such astransitions between neural, vascular, and atrial tissue. Fibrillarmyocardial muscle tissue may also be formed by stretching and/ordegeneration of cells leading to poor connections between such damagedtissue. In row A, the first column shows the homogenous or uniformactivation of compact myocardial muscle tissue during depolarization ofthe heart wall. In the second column, however, the irregular activationof fibrillar myocardial muscle tissue is shown during depolarization inwhich a wave travels at different rates through different strands orportions of the fibrillar myocardial muscle tissue, thus causingasynchronous contraction in different portions of the myocardium.

In row B, time-domain electrogram signals are shown for the compactmyocardial muscle tissue and the fibrillar myocardial muscle tissueduring a depolarization phase of a heartbeat. As shown in FIG. 8, thetime-domain electrogram signals typically comprise a biphasic ortriphasic shape for compact myocardial muscle tissue (shown in column 1)and a more polyphasic shape for fibrillar myocardial muscle tissue(shown in column 2). Finally, the frequency-domain of the electrogramsignals of row B for compact myocardial muscle tissue and fibrillarmyocardial muscle tissue is shown in row C. The frequency-domain isobtained by performing an FFT on a time period of the time-varyingelectrograms shown row B, column 1 for compact myocardial muscle tissueand row B, column 2 for fibrillar myocardial muscle tissue. As shown inrow C of FIG. 8, the frequency spectrum for compact myocardial muscletissue typically comprises a higher amplitude at a single peak locatedaround a fundamental frequency, while the frequency spectrum for thefibrillar myocardial muscle tissue typically comprises a lower amplitudeat its fundamental frequency due to a right-shift of the frequencycaused by a number of harmonic frequency components.

As shown in FIG. 8, fibrillar myocardial muscle tissue can lead toirregular wavefronts of electrical activity during depolarization of theheart. The greater the ratio of fibrillar myocardial muscle tissue tocompact myocardial muscle tissue, the more likely there is a propensityfor atrial fibrillation. In such areas “atrial fibrillation nests” (or“AFIB nests”) may be identified as potential sources of atrialfibrillation. Thus, by use of frequency-domain information, a physicianmay be able to further identify potential trouble spots that may lead toatrial fibrillation.

Various numerical indices can be obtained from the frequency spectrum ofthe electrogram signal. Any of these indices can then be mapped to athree-dimensional model of a patient's heart to allow a user such as aphysician to identify locations on the wall of the heart that correspondto a particular characteristic. In one exemplary variation of thepresent invention, a dominant frequency of an electrogram signal can beidentified in the frequency spectrum, which has been obtained via a FFT.As can be seen in FIG. 9A, for example, a typical normal, or compact,myocardial muscle tissue may have a single peak in the spectrum, while afibrillar myocardial muscle tissue has more spectral peaks than does acompact myocardial muscle tissue. The number of spectral peaks may bedetermined for multiple points around the wall of the heart on athree-dimensional model as described above. (FIGS. 7-9 a are associatedwith an article by PACHON, Jose, C., et. al., A new treatment for atrialfibrillation based on spectral analysis to guide the catheterRF-ablation, Europace, (2004) 6, 590-601, The European Society ofCardiology.)

In another variation of the present invention, a maximum peak amplitudeat the dominant frequency may be determined from the frequency spectrumof the electrogram signal and may be mapped to a three-dimensional modelof the heart. In FIG. 9A, for example, the maximum peak amplitude at thedominant frequency of compact myocardial muscle tissue can be seen to behigher at about 175 dB mV, while the maximum peak amplitude at thedominant frequency of fibrillar myocardial muscle tissue is lower atabout 80 dB mV. These values may also be mapped onto a three-dimensionalmodel of the heart.

In yet another variation, a ratio of energy in one band of thefrequency-domain to the energy in a second band of the frequency-domainmay be determined and mapped to a three-dimensional model of the heart.For example, FIG. 9B shows the ratio of energy in the passband of 60 to240 Hz to the energy below 60 Hz is higher for the spectrum ofelectrograms from fibrillar myocardial muscle tissue than in thespectrum of electrograms from compact myocardial muscle tissue.

While examples of time-domain and frequency-domain information have beendescribed herein as able to be translated to a three-dimensional map ofa patient's heart, one skilled in the art would recognize that othertime- and frequency-domain information may also be determined and mappedto a three-dimensional model. For example, the following information maybe determined from the time-domain or frequency-domain and mapped to athree-dimensional model: a low-frequency or high-frequency passband ofinterest (e.g., in Hz); a frequency with the maximum energy in apassband (e.g., in Hz); a number of peaks within a passband (e.g., acount); an energy, power, and/or area in each peak (e.g., dB); a ratioof energy and/or area in each peak to that in another passband; and awidth of each peak in a spectra (e.g., in Hz).

FIG. 10 shows one example of a method for determining information from atime-varying electrogram in the time-domain and/or frequency-domain andmapping that information onto a three-dimensional model (e.g., a heart).In operation 100, a number of electrodes (e.g., contact or non-contact,unipolar or bipolar mapping electrodes) are used to sample atime-varying electrogram signal. The electrogram signal, for example,may be sampled for multiple sites along the wall of the heart and/or thesurrounding vasculature.

An FFT is then performed over a time period of the time-varyingelectrogram to determine frequency-domain information for thatelectrogram in operation 102. A real-time display of the time-domainand/or frequency-domain information may be displayed in operation 104.One or more parameters are then determined in operation 106. Exemplaryparameters are described above and include, for example, a timedifference between a roving electrode and a reference electrode; thepeak-to-peak voltage of the roving electrode; the peak negative voltageof the roving electrode; CFE information; a dominant frequency of anelectrogram signal; a maximum peak amplitude at the dominant frequency;a ratio of energy in one band of the frequency-domain to the energy in asecond band of the frequency-domain; a low-frequency or high-frequencypassband of interest; a frequency with the maximum energy in a passband;a number of peaks within a passband; an energy, power, and/or area ineach peak; a ratio of energy and/or area in each peak to that in anotherpassband; and a width of each peak in a spectrum. Colors, shades ofcolors, and/or grayscales are assigned to values of the parameters to beidentified in operation 108, and colors, shades of colors, and/orgrayscales corresponding to the parameters for the electrograms sampledby the electrodes are updated on a three-dimensional model (e.g., of aheart) continuously and in real time in operation 110.

One particular area of interest is the mapping of areas of the heartcomprised of autonomic nerve cells. ECG information may be mapped toidentify the foci of electrical propagation through the heart. Theinitiation points for electrical signals will generally be autonomiccell bundles, or ganglia plexi. To the extent that any arrhythmia iscaused by a malfunction in autonomic cells, the ability to detect thismalfunction can significantly aid in the efficacy of treatment andminimize the scope of treatment. A particular advantage to mapping thecomplex fractionated electrograms in the frequency-domain is the abilityto quickly identify and locate such areas of arrhythmia. For example, ifit is determined that a specific autonomic bundle is the source offibrillation, targeting this area of initial neural input instead oftreating multiple areas of fibrillar tissue can substantially reduce thenumber of lesions required to treat the condition.

As discussed above, electrophysiology data can be very useful inlocating tissue that may require treatment. A challenge, however, existswith mapping the electrophysiology data onto the three dimensional modelof the heart. A projection process in accordance with the presentinvention will now be described.

As described above, the electrodes of at least one EP catheter are movedover the surface of the heart and while in motion they detect theelectrical activation of the heart or other EP signals on the surface ofthe heart. During each measurement, the real-time location of thecatheter electrode is noted along with the value of the EP voltage orsignal. The collection of location points and the associatedmeasurements are referred to herein as the “EP data set.” This data isthen projected onto a surface of the three-dimensional modelcorresponding to the location of the electrode when the sampled EP datawas taken. Since this model was not created while the locating surfaceelectrodes are energized, a projection process may be used to place theelectrical information on the nearest heart surfaces represented by thegeometry. In one exemplary embodiment, for example, each point on thesurface of the three-dimensional model is colored or gray-shadedaccording to the value of the single nearest location in the EP dataset. This new point is used as the “location” for the presentation of EPdata in the images presented to the physician.

In another embodiment, the EP data is mapped onto the three-dimensionalmodel using a new and improved technique. Because the EP data ismeasured at points that may not be the same set of physical locationsused to generate the three-dimensional model, the EP data must beprojected onto a surface of the three-dimensional model. In thispreferred embodiment, the EP data is projected onto thethree-dimensional model for display purposes. The EP data values (peakvoltage, activation time, maximum frequency, or other quantities) mustalso be interpolated onto the points of the three-dimensional geometry.Once the EP data is projected onto the three-dimensional model, the EPdata may be converted into colors and rendered according to standardcomputer graphics techniques. A way to relate the three-dimensionalmodel to the EP data structure must be determined. For manysurface-interpolation problems, it is desirable to generate a goodtriangulation of the data points—connecting them into triangles whichfill the x-y plane (in 2D). Then the data value can be approximated atany point in the plane using a smoothly weighted average of the threeendpoints of its triangle. This triangular based interpolation is knownas barycentric interpolation, although it is contemplated that otherknown methods of interpolation could be used. In ordinary 2D space, aparticular triangulation called the Delaunay triangulation is commonlyused and is known to give optimal results. The Delaunay triangulation isclosely related to the Voronoi diagram, the set of regions surroundingeach data point that are closer to that data point than any other. Inparticular, each pair of data points whose Voronoi regions border eachother is connected by an edge in the Delaunay triangulation. But it isbelieved that there are no known algorithms for computing a Delaunaytriangulation on arbitrary and complex surfaces such as thethree-dimensional models of the heart as described in connection withthis invention. The method of this preferred embodiment computes a goodapproximation to the Delaunay triangulation as follows. Each EP datapoint is projected to its closest point on the three-dimensional model,and those projected points are searched to determine Voronoi neighbors.A vertex is selected in the three-dimensional model, and the EP data mapis searched for the two EP data points that are closest to the vertex inthe three-dimensional model. Generally, the EP data points that areneighboring the selected vertex are searched first, and then generally,the neighbors of neighbors are searched, until the two closest EP datapoints are found. With high likelihood, those data points have Voronoiregions that border each other, and so the two points are connected witha Delaunay edge. The process is repeated for each of the other verticesin the three-dimensional model. Then, a plurality of triangles areformed out of this set of Delaunay edges, knowing that each edge shouldbe part of exactly two triangles. If the resulting triangulation has any“holes”—cycles of four or more edges not containing any triangles—theholes may be filled by recursively adding the shortest new edgeconnecting two data points of the cycle. This is necessary because thetwo-closest-data-point algorithm may not discover every Delaunay edge,although nearly all edges it does discover turn out to be Delaunayedges. Once the EP data points have been have been collected into thistriangulation, the measured data may be interpolated onto each vertex ofthe three-dimensional model. Most vertices will be interior to one ofthe Delaunay triangles, and will be interpolated using EP data measuredat each of the triangle's three data points. Some vertices may besufficiently close to a triangle edge (e.g., it lies on or very close tothe triangle edge), such that the value to be assigned will bebi-linearly interpolated from the respective measurements of the twoendpoints. Preferably, a threshold may be set to dictate how close thevertex must be to an edge before bilinear interpolation is applied. Afew vertices may be closer to a data point than any edge or triangle, inwhich case, the vertices will be assigned the same EP data as the closedata point. Preferably, a threshold may be set to dictate how close thevertex must be to a measurement point before the value of themeasurement point will be assigned. Once EP data values have beenassigned to a plurality of points in the three-dimensional model, then arobust color map may be generated, and preferably, the color map issmoothed using a smoothing algorithm to provide a clinically reasonablecolor rendering, one in which the points in the three-dimensional modelget their color only from measurements that were taken at nearbymeasurement points.

The embodiment described in the previous paragraph will now be discussedin the context of FIGS. 11-14. FIG. 11 is a three-dimensional model of aportion of a heart, in which the location points 91 have been connectedusing triangulation. This surface may be re-sampled over a more uniformgrid and further may be interpolated to give a reasonably smooth surfacestored as a three dimensional model for presentation to the physicianduring the same or a later procedure. The re-sampled surface generallyhas a greater number of data points. The resampled surface may also beprocessed using a smoothing algorithm, which will give the geometry asmoother appearance. Such a three dimensional model, for example,provides an estimated boundary of the interior of the heart region fromthe set of points. Markers 92 which represent data measurement pointswithin an EP data set have been superimposed upon the three-dimensionalmodel in FIG. 11. As previously explained, the locations of the datameasurement points (represented by markers 92) for the EP data setgenerally are not at the same locations as location points 91. Thus,markers 92 are sometimes located wholly within a triangle, and othertimes, appear on or near an edge of a triangle.

FIG. 12 shows the EP data set which comprises a series of measurementpoints 93, each of which has a corresponding voltage level. The voltagelevel is represented by marker 92, whose color is varied to indicate thevoltage level.

Understanding that the EP data set depicted in FIG. 12 is the sameoverall geometry as that of FIG. 11, it may be visualized that themeasurement points 93 of the EP data set, though generated using thesame region of the same heart, do not correspond to the location points91 of the three-dimensional model. It is the lack of a one-to-onepositional correspondence that generates a need to project the measuredEP data onto the three-dimensional model. To assist in the projectionprocess, a location point 91 is selected from the plurality of locationpoints 91 that comprise the three-dimensional model of FIG. 11. Next,the location of the selected location point 91 is compared to thelocation of at least a subset of the plurality of measurement points 93in order to determine which are the two measurement points 93 that areclosest to the selected location point 91. The pair of closestmeasurement points are deemed to form a Delaunay edge 94 (which isdepicted by a green line on FIG. 12); it is highly likely that theidentified pair of closest measurement points 93 are Voronoi neighbors.The closest measurement points may be identified using any number ofalgorithms designed to evaluate distances, including, for example, aKirsanov-Hoppe or Fast Marching geodesic algorithm. The identificationof pairs of measurement points based on their proximity to selectedlocation points may be repeated to identify additional Delaunay edges.In the process of assessing closest pairs of measurement points for eachlocation point, a plurality of triangles will likely be formed. If afterthis algorithm, there remain location points which are not part of atriangle, then triangular relationships may be formed by drawing linesto the other measurement points, giving preference to those measurementpoints which may be connected using shortest distance lines (withpreferences given to the creation of triangle edges that are shorter inlength).

While the proximity relationships between selected location points 91and their respective pairs of closest measurement points 93 may betracked in a variety of ways, the relationship are depicted graphicallyin both FIG. 12 and FIG. 13. On FIG. 12, the midpoints 95 of mostDelaunay edges have at least one, and typically, several lines (theyappear in dark, red ink) that contact the midpoint 95. These linesrepresent connections to various location points in thethree-dimensional model. The existence of a line to a particularlocation point means that for that particular location point, it wasdetermined that the pair of closest measurement points was the pair thatforms the identified Delaunay edge. The same red lines are shown inFIGS. 12 and 13, but FIG. 12 shows them with the Delaunay edges and FIG.13 with the three-dimensional model. FIG. 13 contains thethree-dimensional model of FIG. 11 upon which distance lines have beenimposed to identify the associations between selected location points inthe three- dimensional model and the Delaunay edges that are closest tothe selected location points. These associations are used when themeasured data of the EP map is projected onto the location points of thethree-dimensional model. These red lines only determine which Delaunayedges are used in the triangulation; they are not used to indicate fromwhich Delaunay edges the various location points of thethree-dimensional model are interpolated.

The actual projection of EP data values will be described next. Eachlocation point in the three-dimensional model is assessed relative tothe triangles that have been used to model the EP data set.Conceptually, if the three-dimensional model is superimposed on thetriangulated model of the EP data set, the relationship between thelocation points and the triangles is much easier to visualize. Mostlocation points 91 will be within the interior of one of the trianglesof the triangulated model of the EP data set, and the EP data value tobe assigned to such location points 91 may be interpolated usingbarycentric interpolation based on the measured values of the threevertices (the measurement locations 93) of the triangle. Barycentricinterpolation is known in the art, and is a preferred method. However,it is contemplated that other known methods of interpolation could beused as well. Some location points 91 may be so close to a triangle edge(e.g., it lies on or very close to the triangle edge), such that thevalue to be assigned will be bi-linearly interpolated from therespective measured EP data values of the two endpoints of the edge. Afew location points 91 may be closer to a measurement point than anyedge or triangle, in which case, the location points 91 will be assignedthe same EP data value as was measured at the closest measurement point.Once EP data values have been assigned to a plurality of points in thethree-dimensional model (and preferably, all of the location points ofthe three-dimensional model), then the three-dimensional model (and itscorresponding assigned EP data values) may be submitted to a coloringprogram which can color the three-dimensional model based on itsassigned EP data levels (e.g., peak voltage, activation time, maximumfrequency, or other quantities). FIG. 14 represents the output from acoloring program, wherein the coloring represents different voltagelevels that were assigned by projecting the EP data map of FIG. 12 ontothe three-dimensional model of FIG. 11.

In yet another embodiment, the EP data is mapped onto thethree-dimensional model using a technique involving subdividing thethree-dimensional model. Specifically, the three-dimensional model issubdivided using triangulation in such a way as to make all EP datapoints vertices in a subdivided three-dimensional model. Then, thesubdivided three-dimensional model may be processed using amesh-coarsening or decimation algorithm that allows one to specify theoutput vertex set—which will be specified as being exactly the set of EPdata points. The decimation program may then decide the properconnectivity for the points on the three-dimensional model. It ispreferred in this embodiment that each vertex in the EP data beprojected onto the closest vertex or edge of the subdividedthree-dimensional model using the Kirsanov-Hoppe or Fast Marchinggeodesic algorithm. The output of the decimation program may then besubmitted to a coloring program which can color the three-dimensionalmodel based on its voltage levels. It is also contemplated that Delaunayedges that are longer than a predetermined distance threshold bedisallowed.

Although multiple embodiments of this invention have been describedabove with a certain degree of particularity, those skilled in the artcould make numerous alterations to the disclosed embodiments withoutdeparting from the spirit or scope of this invention. For example, whilethe description above describes data being mapped to a three-dimensionalmodel, data may be mapped to any map including, but not limited to, atwo- or three-dimensional, static or time-varying image or model. Alldirectional references (e.g., upper, lower, upward, downward, left,right, leftward, rightward, top, bottom, above, below, vertical,horizontal, clockwise, and counterclockwise) are only used foridentification purposes to aid the reader's understanding of the presentinvention, and do not create limitations, particularly as to theposition, orientation, or use of the invention. Joinder references(e.g., attached, coupled, connected, and the like) are to be construedbroadly and may include intermediate members between a connection ofelements and relative movement between elements. As such, joinderreferences do not necessarily infer that two elements are directlyconnected and in fixed relation to each other. It is intended that allmatter contained in the above description or shown in the accompanyingdrawings shall be interpreted as illustrative only and not limiting.Changes in detail or structure may be made without departing from thespirit of the invention as defined in the appended claims.

1. A method for mapping electrophysiological information on athree-dimensional model comprising: A) obtaining a three-dimensionalmodel of a portion of an anatomy comprising position information for aplurality of location points on a surface of the portion of the anatomy;B) obtaining an electrophysiology map comprising position informationfor a plurality of measurement points and electrophysiology measurementsmade at each of the plurality of measurement points; C) choosing alocation point from the plurality of location points in thethree-dimensional model and determining a pair of closest measurementpoints from the electrophysiology map; D) defining an edge between thepair of closest measurement points; E) repeating steps C) and D) for atleast a first subset of the plurality of location points in thethree-dimensional model, thereby defining a plurality of edgesconnecting at least some of the plurality of measurement points withinthe electrophysiology map; F) defining a plurality of polygons from theplurality of edges; and G) identifying one of the plurality of locationpoints from the three-dimensional model, identifying one of theplurality of polygons whose edges surround the identified locationpoint, and assigning an electrophysiology level to the identifiedlocation point using electrophysiology measurements measured at one ormore vertices of the identified polygon.
 2. The method according toclaim 1, wherein the step of assigning an electrophysiology level to theidentified location point using electrophysiology measurements measuredat one or more vertices of the identified polygon comprises assigning anelectrophysiology level to the identified location point usingbarycentric interpolation.
 3. The method according to claim 1, whereinthe step of assigning an electrophysiology level to the identifiedlocation point using electrophysiology measurements measured at one ormore vertices of the identified polygon comprises: identifying a closestedge of the identified polygon to the identified location point; andassigning an electrophysiology level to the identified location pointusing linear interpretation.
 4. The method according to claim 1, whereinthe step of assigning an electrophysiology level to the identifiedlocation point using electrophysiology measurements measured at one ormore vertices of the identified polygon comprises: identifying a closestvertex of the identified polygon to the identified location point; andassigning the identified location point an electrophysiology level equalto an electrophysiology level at the closest vertex.
 5. The methodaccording to claim 1, further comprising repeating step G) for at leasta second subset of the plurality of location points in thethree-dimensional model.
 6. The method according to claim 5, furthercomprising: assigning a color or grayscale to each location point withinthe second subset of the plurality of location points based on arelative magnitude of the electrophysiology level assigned to eachlocation point within the second subset of the plurality of locationpoints; and presenting the three-dimensional model using the colors orgrayscales assigned to each location point within the second subset ofthe plurality of location points.
 7. The method according to claim 1,wherein the step of obtaining an electrophysiology map comprises:inserting an electrode into a patient; placing the electrode at aplurality of measurement points; receiving position information for eachof the plurality of measurement points; receiving electrophysiologymeasurements at each of the plurality of measurement points; andassociating the electrophysiology measurements with the respectivemeasurement points at which the electrophysiology measurements weremeasured.
 8. The method according to claim 1, wherein the step ofobtaining a three-dimensional model of a portion of an anatomycomprises: inserting an electrode into a patient; placing the electrodeat a plurality of location points within the patient; receiving positioninformation for each of the plurality of location points; and generatinga three-dimensional model of a portion of an anatomy comprising positioninformation for each of the plurality of location points.
 9. The methodaccording to claim 1, wherein the step of defining a plurality ofpolygons from the plurality of edges comprises defining a plurality oftriangles from the plurality of edges.
 10. The method according to claim1, wherein the step of obtaining a three-dimensional model of a portionof an anatomy comprises using an electrical-field based localizationsystem to generate the three-dimensional model of the portion of theanatomy.
 11. A system for mapping electrophysiological information on athree-dimensional model, the system comprising: a modeling processor togenerate a three-dimensional model of at least a portion of an anatomycomprising position information for a plurality of location points on asurface of the portion of the anatomy; an electrophysiology measurementdevice for generating an electrophysiology map comprising positioninformation for a plurality of measurement points and electrophysiologymeasurements made at the plurality of measurement points, theelectrophysiology measurements being associated with the respectivemeasurement points at which they were measured; an edge processor toprocess at least a first subset of the plurality of location points onthe surface of the anatomy; to determine, for each location point withinthe first subset of the plurality of location points, a pair of closestmeasurement points in the electrophysiology map; and to define an edgeconnecting the pair of closest measurement points; a geometry processorto define a plurality of polygons from a plurality of edges defined bythe edge processor; and a projection processor to assign anelectrophysiology level to each location point within a second subset ofthe plurality of location points based upon electrophysiologymeasurements measured at one or more vertices of a polygon from theplurality of polygons surrounding each location point within the secondsubset of the plurality of location points.
 12. The system according toclaim 11, wherein the projection processor assigns an electrophysiologylevel to each location point within the second subset of the pluralityof location points based upon barycentric interpolation.
 13. The systemaccording to claim 11, wherein the projection processor assigns anelectrophysiology level to each location point within the second subsetof the plurality of location points based upon linear interpolation. 14.The system according to claim 11, wherein the geometry processor definesa plurality of triangles from the plurality of edges defined by the edgeprocessor.